Color region based recognition of unidentified objects

ABSTRACT

A machine implemented method is disclosed. The method includes characterizing an object by color regions, and then identifying the object in accordance with at least the color region based characterization of the object. In one embodiment, the method further includes generating output response, such as audio response, in accordance with the identification result.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to the field of computer systems. Inparticular, the present invention relates to object recognition bycomputer systems.

2. Background Information

As advances in microprocessor and other related technologies continue toimprove the price/performance of various electronic components in recentyears, powerful multi-media personal computers (PC) that once werewithin the exclusive realm of mainframe computers have now becomeincreasingly affordable to the average consumers. More and more homesand classrooms are now equipped with PC for business, education, and/orentertainment purposes.

Numerous advances have also been made in the field of computer vision,i.e. the ability to recognize people, objects, etc., by computers.However, perhaps due to the fact that much of the original interest wasmotivated by security applications, the techniques known today aregenerally too computationally intensive (or unnecessary) for use byclassroom/home PCs for more casual applications such as education and/orentertainment. Thus, a less computationally intensive and yetsufficiently effective object recognition technique for causalapplications is desired.

SUMMARY OF THE INVENTION

A machine implemented method is disclosed. The method includescharacterizing an object by color regions, and then identifying theobject in accordance with at least the color region basedcharacterization of the object.

In one embodiment, the method further includes generating outputresponses, such as audio responses, in accordance with theidentification result.

BRIEF DESCRIPTION OF DRAWINGS

The present invention will be described by way of exemplary embodiments,but not limitations, illustrated in the accompanying drawings in whichlike references denote similar elements, and in which:

FIG. 1 illustrates an overview of the present invention including thecolor region based object recognition tool of the present invention;

FIG. 2 is a flow chart illustrating one embodiment of the operationalflow of the color based characterization portion of the objectrecognition tool;

FIG. 3 is a flow chart illustrating in further detail one embodiment ofthe step of subsetting an image of an object into color regions;

FIG. 4 is a flow chart illustrating one embodiment of the operationalflow of the inference portion of the object recognition tool;

FIG. 5 illustrates an exemplary application of the present invention;and

FIG. 6 is a block diagram illustrating a hardware view of one embodimentof a computer suitable for use to practice the present invention.

DETAILED DESCRIPTION OF THE INVENTION

In the following description, various aspects of the present inventionwill be described. Those skilled in the art will also appreciate thatthe present invention may be practiced with only some or all aspects ofthe present invention. For purposes of explanation, specific numbers,materials and configurations are set forth in order to provide athorough understanding of the present invention. However, it will alsobe apparent to one skilled in the art that the present invention may bepracticed without the specific details. In other instances, well knownfeatures are omitted or simplified in order not to obscure the presentinvention.

Parts of the description will be presented in terms of operationsperformed by a computer system, using terms such as data, flags, bits,values, characters, strings, numbers and the like, consistent with themanner commonly employed by those skilled in the art to convey thesubstance of their work to others skilled in the art. As well understoodby those skilled in the art, these quantities take the form ofelectrical, magnetic, or optical signals capable of being stored,transferred, combined, and otherwise manipulated through mechanical andelectrical components of the computer system; and the term computersystem include general purpose as well as special purpose dataprocessing machines, systems, and the like, that are standalone, adjunctor embedded.

Various operations will be described as multiple discrete steps in turnin a manner that is most helpful in understanding the present invention,however, the order of description should not be construed as to implythat these operations are necessarily order dependent, in particular,the order of their presentations.

Referring now to FIG. 1, a block diagram illustrating one embodiment ofthe present invention is shown. As illustrated, object recognition tool100 includes color based characterization portion 102 and inferenceportion 104. As will be described in more detail below, color basedcharacterization portion 102 characterizes an object, such as object106, based on color regions of the object, and inference portion 104 inturn identifies the object in accordance with at least the color regionbased characterizations. In one application of the present invention,the identification result is provided to application 108, which in turnresponds to the identification results.

Object 106 is intended to represent all physical items that are visuallyobservable. It includes but is not limited to physical items such as asculpture, a painting, a desk, a table, a fork, a knife, a vase, astuffed animal, a doll, a book, a page in a book, a flash card, and soforth. Application 108 is intended to represent a broad range ofbusiness, education and entertainment applications. The response to theidentification result may be externalized, e.g. an audio response,internal only, e.g. changing certain state data, or both.

FIG. 2 illustrates one embodiment of the operational flow of color basedcharacterization portion 102. As shown, for the illustrated embodiment,color based characterization 102 first generates digitized image data ofobject 106, e.g. in the form of a frame of video signals, step 202. Inone embodiment, the digitized image data are generated as RGB pixeldata. In an alternate embodiment, the digitized image data are generatedas YUV pixel data instead. Next, color based characterization 102transforms the pixel data from the RGB/YUV space to the HSI space, step204. In one embodiment, like variant colors are also transformed intotheir primary colors to reduce the number of colors, e.g. like variantsof the red color (within a predetermined range of degrees in the Hindex) are all transformed into the red color. Then, color basedcharacterization 102 subsets the image into regions in accordance withthe pixels' transformed colors, step 206.

Step 202 may be performed using any one of a number of techniques knownin the art, e.g. through a video camera and a capture card. Furthermore,the present invention may be performed without performing step 204. Thatis, step 206 may be performed with the pixel data in RGB or YUV space,without transforming the pixel data into the HSI space and withoutcollapsing like variant colors into the primary colors. However,experience has shown that the HSI space appears to provide the mostconsistent result across a wide range of ambient conditions, andcollapsing like variant colors into the primary colors reduces theamount of processing without significantly sacrificing the ability toproperly recognize an object.

FIG. 3 illustrates one embodiment of step 206 of FIG. 2. As shown, colorbased characterization portion 102 first selects a pixel at the lowerleft corner of a frame, step 302. Next, color based characterizationportion 102 assigns the pixel to a new color region, step 304.Additionally, color based characterization portion 102 attributes thecolor of the pixel as the color of the new color region, as well asattributing the coordinates of the pixel as the reference coordinates ofthe new color region, and initializing the size of the new color regionto one pixel.

Then, color based characterization portion 102 determines if there is atleast another pixel to the right of the current pixel, step 306. Ifthere is at least another pixel to the right, color basedcharacterization portion 102 selects the pixel immediately to the right,step 308. Upon selecting the pixel immediately to the right, color basedcharacterization portion 102 determines if the selected pixel has thesame color as the previous pixel, i.e. the pixel immediately to the leftof the now selected pixel, step 310. If the determination isaffirmative, color based characterization portion 102 assigns theselected pixel to the same color region of the pixel immediately to itsleft, and increments the size of the color region by one pixel, step312; then continues the process at step 306. On the other hand, if thedetermination is negative, color based characterization portion 102determines if the selected pixel has the same color as the pixelimmediately below it, step 314. If the determination is affirmative,color based characterization portion 102 assigns the pixel to the samecolor region of the pixel immediately below it, attributes thecoordinates of the selected pixel as the reference coordinates of thecolor region instead, and increments the size of the color region by onepixel, step 316; then continues the process at step 306. On the otherhand, if the determination is negative, color based characterizationportion 102 continues the process at step 304, i.e. assigning theselected pixel to a new color region, attributing the coordinates of theselected pixel as the reference coordinates of the new color region, andinitializing the size of the new color region to one pixel.

Eventually, at step 306, color based characterization portion 102determines there are no more pixels to the right. Color basedcharacterization portion 102 then continues the process at step 318wherein it determines if there are pixels above the last processedpixel. If the determination is affirmative, color based characterizationportion 102 selects the left most pixel from the row of pixelsimmediately above, step 320. Upon doing so, color based characterizationportion 102 continues the process at step 314 as described earlier.

Eventually, at step 310, color based characterization portion 102determines there are no more pixels above either, i.e. all pixels of theentire frame have been processed. At such time, the process terminates.

In alternate embodiments, the pixels may be processed in orders otherthan the left to right and bottom to top manner described earlier.Furthermore, other coordinates beside the coordinates of the top leftpixel may be used as the reference coordinates of a color regioninstead, as well as other metrics may be employed to denote the size ofa color region.

FIG. 4 illustrates one embodiment of the operational flow of inferenceportion 104. As shown, for the illustrated embodiment, inference portion104 infers the identity of the characterized object by examining anumber of color region characterized reference objects of knownidentities, one at a time. At step 402, a color region characterizedreference object of known identity is selected. The color regioncharacterized reference object is analyzed to determine if it containsat least the same number of color regions for each of the differentcolors as the characterized object whose identity is being determined,step 404. If the color region characterized reference object does notcontain at least the same number of color regions for each of thedifferent colors, the color region characterized reference object isrejected, step 412, and the process continues at step 414. For example,if the object whose identity is being determined is characterized ashaving two red color regions and one blue color regions, then a colorregion characterized reference object must contain at least two redcolor regions and at least one blue color region, otherwise the colorregion characterized reference object is rejected.

Next, the color region characterized reference object is analyzed todetermine if the color regions of each of the color groups having atleast the same number of color regions have sizes that are at least aslarge as the color regions of the characterized object whose identity isbeing determined, step 406. If the color regions of each of the colorgroups having at least the same number of color regions do not havecolor regions with the requisite sizes, the color region characterizedreference object is rejected, step 412, and the process continues atstep 414. For example, if the object whose identity is being determinedis characterized as having two red color regions of sizes s1 and s2 andone blue color regions of size s3, then a color region characterizedreference object must contain at least two red color regions with sizesthat are at least s1 and s2, and at least one blue color region with asize that is at least s3, otherwise the color region characterizedreference object is rejected.

Then, the color region characterized reference object is analyzed todetermine if the color regions of interest have the same relativeorientation to each other as the color regions of the characterizedobject whose identity is being determined, step 408. If the color regioncharacterized reference object does not contain color regions with thesame relative orientation to each other, the color region characterizedreference object is rejected, step 412, and the process continues atstep 414. In one embodiment, the color regions' relative orientation toeach other is determined using the reference coordinates of the colorregions. For example, if the object whose identity is being determinedis characterized as having two red color regions of sizes s1 and s2 andone blue color regions of size s3, occupying a substantially equilateraltriangular orientation (in accordance with their reference coordinates),then a color region characterized reference object must contain at leasttwo red color regions with sizes at least that of s1 and s2, and atleast one blue color region with a size that is at least s3, occupyingalso a similar equilateral triangular orientation (i.e. within certainpredetermined tolerance margins), otherwise the color regioncharacterized reference object is rejected. In one embodiment, thepredetermined tolerance margins are configurable at set up. In analternate embodiment, the predetermined tolerance margins are userconfigurable during operation.

For the illustrated embodiment, if the color region characterizedreference object is not rejected at step 408, the determination processterminates, and the identity of the reference object is considered to bethe identity of the characterized object, step 410. At step 414, it isdetermined that whether there are additional reference objects. If thereare still additional reference objects available for analysis, theprocess continues at step 402, otherwise inference portion 104 reportsthat it is unable to determine the identity of the characterized object,step 416, and the process terminates.

The number of reference objects to be employed is application dependent.Obviously, if more reference objects are employed, then it is lesslikely that inference portion 104 will be unable to identify an object.In one embodiment, where the number of referenced objects employed isrelatively small, all referenced objects are analyzed before a finalinference is drawn. While experience has shown merely employing theabove described criteria, inference portion 104 is able to effectivelyrecognize objects with a reasonable level of accuracy for a large numberof casual applications, those skilled in the art will appreciate that inalternate embodiments, additional criteria may be employed to reduce thelikelihood of incorrect inference by inference portion 104.

FIG. 5 illustrates an exemplary application of the present application.As illustrated, the application includes the use of multi-media computer500 to read book 502 for a user. Multi-media computer 500 includesmulti-media resources such as video camera 504, a video capture card(not visible), speakers 506, and an audio player (not shown). Moreimportantly, multi-media computer 500 is equipped with the color regionbase object recognition tool 100 of the present invention describedearlier, and color region characterization as well as audio data foreach page of book 502. During operation, the color region based regionobject recognition tool 100 of the present invention identifies thecurrent page book 502 is open to, based at least in part on the colorregion characterization of the page, using the video image generated byvideo camera 504 and the associated capture card, and the pre-storedreference color region characterization for each page of the book. Inresponse, the audio player plays the audio data for the page, therebyreading the page for the user.

In one embodiment, multi-media computer 500 is provided with colorregion characterization and audio data for a number of books, andmulti-media computer 500 is further provided with a user interface forthe user to inform multi-media computer 500 of the identity of the book,thereby allowing object recognition tool of the present invention toemploy the appropriate reference color region characterizations. In analternate embodiment, the reference color region characterizations areorganized by the books, and include color region characterizations forthe covers of the books. The object recognition tool 100 of the presentinvention is further extended to include the selective employment of asubset of the pre-stored reference color region characterizations basedon the identification of the book, through color region characterizationof the cover and comparison with the pre-stored reference color regioncharacterizations for the covers.

FIG. 6 illustrates a hardware view of one embodiment of a computersystem suitable for practicing the present invention, including theabove described application. As shown, for the illustrated embodiment,computer system 600 includes processor 602, processor bus 606, highperformance I/O bus 610 and standard I/O bus 620. Processor bus 606 andhigh performance I/O bus 610 are bridged by host bridge 608, whereas I/Obuses 610 and 612 are bridged by I/O bus bridge 612. Coupled toprocessor bus 606 is cache 604. Coupled to high performance I/O bus 610are camera, 611, system memory 614 and video memory 616, against whichvideo display 618 is coupled. Coupled to standard I/O bus 620 are diskdrive 622, keyboard and pointing device 624, communication interface626, and speakers 628.

These elements perform their conventional functions known in the art. Inparticular, disk drive 622 and system memory 614 are used to storepermanent and working copies of color region based object recognitiontool of the present invention, as well as color region characterizationof reference objects and applications that use the color region basedobject recognition tool. The permanent copies may be pre-loaded intodisk drive 622 in factory, loaded from distribution medium 632, or downloaded from a remote distribution source (not shown). The constitutionsof these elements are known. Any one of a number of implementations ofthese elements known in the art may be used to form computer system 600.

In general, those skilled in the art will recognize that the presentinvention is not limited by the details described, in particular, thepresent invention is not limited to the exemplary application, instead,the present invention can be practiced with modifications andalterations within the spirit and scope of the appended claims. Thedescription is thus to be regarded as illustrative instead ofrestrictive on the present invention.

Thus, a method and apparatus for color region based object recognitionand application has been described.

What is claimed is:
 1. A method comprising: capturing an image of eachof a plurality of known objects; characterizing each image of theplurality of known objects by dividing each image into a plurality ofcolor regions; capturing an image of an unidentified object;characterizing the image of the unidentified object by dividing theimage of the unidentified object into a plurality of color regions; andidentifying the unidentified object at least in part by: comparing thecolor regions of the image of the unidentified object with the colorregions of one or more of the images of the plurality of known objects;comparing the number of color regions of each color in the image of theunidentified object to the number of color regions of each color in theimage of the first known object; comparing the size of each color regionof each color in the image of the unidentified object to the size ofeach color region of each color in the image of the first known object;and comparing the relative orientation of each color region of eachcolor in the image of the unidentified object to the relativeorientation of each color region of each color in the image of the firstknown object.
 2. The method of claim 1, wherein identifying theunidentified object further comprises rejecting the first known objectas the identity of the unidentified object if the number of colorregions, the size of color regions, or the relative orientation of colorregions of the image of the unidentified object and the image of thefirst known object do not match within predetermined tolerances.
 3. Themethod of claim 1, wherein characterizing the image of the unidentifiedobject by dividing the image into a plurality of color regionscomprises: identifying the color of each of a plurality of pixels of theimage; and assigning each of the plurality of pixels of the image to oneof the plurality of color regions of the image.
 4. The method of claim3, wherein characterizing the image of the unidentified object bydividing the image into a plurality of color regions further comprises:selecting a first pixel of the plurality of pixels of the image andassigning the first pixel to a first color region; establishing thecolor of the first pixel as the color of the first color region;establishing the coordinates of the first pixel as the referencecoordinates of the first color region; selecting a second pixel of theplurality of pixels of the image, wherein the second pixel is adjacentto the first pixel; if the second pixel is the same color as the firstpixel, assigning the second pixel to the first color region; and if thecolor of the second pixel is different than the color of the firstpixel: assigning the second pixel to a second color region, establishingthe color of the second pixel as the color of the second color region,and establishing the coordinates of the second pixel as the referencecoordinates of the second color region.
 5. The method of claim 4,wherein characterizing the image of the unidentified object by dividingthe image into a plurality of color regions further comprises examiningeach of the remaining pixels of the plurality of pixels of the image andassigning each remaining pixel either to a color region of an adjacentpixel or to a new color region.
 6. The method of claim 1, furthercomprising generating digital image data for the unidentified object. 7.The method of claim 1, wherein the unidentified object comprises athree-dimensional object.
 8. The method of claim 1, wherein capturingthe image of the unidentified object comprises capturing the image ofthe unidentified object as a frame of video signals.
 9. The method ofclaim 1, further comprising generating an output response in accordancewith the result of identifying the unidentified object.
 10. A methodcomprising: capturing an image of each of a plurality of known objects;characterizing each image of the plurality of known objects by dividingeach image into a plurality of color regions; capturing an image of anunidentified object; characterizing the image of the unidentified objectby dividing the image of the unidentified object into a plurality ofcolor regions, comprising: identifying the color of each of a pluralityof pixels of the image, assigning each of the plurality of pixels of theimage to one of the plurality of color regions of the image, selecting afirst pixel of the plurality of pixels of the image and assigning thefirst pixel to a first color region, establishing the color of the firstpixel as the color of the first color region, establishing thecoordinates of the first pixel as the reference coordinates of the firstcolor region, selecting a second pixel of the plurality of pixels of theimage, wherein the second pixel is adjacent to the first pixel, if thesecond pixel is the same color as the first pixel, assigning the secondpixel to the first color region, and if the color of the second pixel isdifferent than the color of the first pixel: assigning the second pixelto a second color region, establishing the color of the second pixel asthe color of the second color region, and establishing the coordinatesof the second pixel as the reference coordinates of the second colorregion; and identifying the unidentified object at least in part bycomparing the color regions of the image of the unidentified object withthe color regions of one or more of the images of the plurality of knownobjects.
 11. The method of claim 10, wherein characterizing the image ofthe unidentified object by dividing the image into a plurality of colorregions further comprises examining each of the remaining pixels of theplurality of pixels of the image and assigning each remaining pixeleither to a color region of an adjacent pixel or to a new color region.12. The method of claim 10, further comprising generating digital imagedata for the unidentified object.
 13. The method of claim 10, whereinthe unidentified object comprises a three-dimensional object.
 14. Themethod of claim 10, wherein capturing the image of the unidentifiedobject comprises capturing the image of the unidentified object as aframe of video signals.
 15. The method of claim 10, further comprisinggenerating an output response in accordance with the result ofidentifying the unidentified object.
 16. An object recognition apparatuscomprising: an image capturing device to capture the image of anunidentified object; a memory having stored therein data representing aplurality of images of known objects, wherein the data includes dataregarding the characterization of each image of the plurality of knownobjects obtained by dividing the image into a plurality of colorregions; and a processor, wherein the operations of the processorinclude: characterizing the image of the unidentified object by dividingthe image of the unidentified object into a plurality of color regions,and identifying the unidentified object at least in part by: comparingthe color regions of the image of the unidentified object with the colorregions of one or more of the images of the plurality of known objects;comparing the number of color regions of each color in the image of theunidentified object to the number of color regions of each color in theimage of the first known object; comparing the size of each color regionof each color in the image of the unidentified object to the size ofeach color region of each color in the image of the first known object;and comparing the relative orientation of each color region of eachcolor in the image of the unidentified object to the relativeorientation of each color region of each color in the image of the firstknown object.
 17. The apparatus of claim 16, wherein the operation ofthe processor identifying the unidentified object further comprisesrejecting the first known object as the identity of the unidentifiedobject if the number of color regions, the size of color regions, or therelative orientation of color regions of the image of the unidentifiedobject and the image of the first known object do not match withinpredetermined tolerances.
 18. The apparatus of claim 16, wherein theoperation of the processor characterizing the unidentified image bydividing the image into a plurality of color regions comprises:identifying the color of each of a plurality of pixels of the image; andassigning each of the plurality of pixels of the image to one of theplurality of color regions of the image.
 19. The apparatus of claim 18,wherein the operation of the processor characterizing the unidentifiedimage by dividing the image into a plurality of color regions furthercomprises: selecting a first pixel of the plurality of pixels of theimage and assigning the first pixel to a first color region;establishing the color of the first pixel as the color of the firstcolor region; establishing the coordinates of the first pixel as thereference coordinates of the first color region; selecting a secondpixel of the plurality of pixels of the image, wherein the second pixelis adjacent to the first pixel; if the second pixel is the same color asthe first pixel, assigning the second pixel to the first color region;and if the color of the second pixel is different than the color of thefirst pixel: assigning the second pixel to a second color region,establishing the color of the second pixel as the color of the secondcolor region, and establishing the coordinates of the second pixel asthe reference coordinates of the second color region.
 20. The apparatusof claim 19, wherein the operation of the processor characterizing theunidentified image by dividing the image into a plurality of colorregions further comprises examining each of the remaining pixels of theplurality of pixels of the image and assigning each remaining pixeleither to a color region of an adjacent pixel or to a new color region.21. The apparatus of claim 16, wherein the operations of the processorfurther comprise generating digital image data of the unidentifiedobject.
 22. The apparatus of claim 16, wherein the unidentified objectcomprises a three-dimensional object.
 23. The apparatus of claim 16,wherein the image capturing device captures the image of theunidentified object as a frame of video signals.
 24. The apparatus ofclaim 16, wherein the operations of the processor further comprisegenerating an output response in accordance with the result ofidentifying the unidentified object.
 25. An object recognition apparatuscomprising: an image capturing device to capture the image of anunidentified object; a memory having stored therein data representing aplurality of images of known objects, wherein the data includes dataregarding the characterization of each image of the plurality of knownobjects obtained by dividing the image into a plurality of colorregions; and a processor, wherein the operations of the processorinclude: characterizing the image of the unidentified object by dividingthe image of the unidentified object into a plurality of color regions,comprising: identifying the color of each of a plurality of pixels ofthe image, assigning each of the plurality of pixels of the image to oneof the plurality of color regions of the image, selecting a first pixelof the plurality of pixels of the image and assigning the first pixel toa first color region; establishing the color of the first pixel as thecolor of the first color region; establishing the coordinates of thefirst pixel as the reference coordinates of the first color region;selecting a second pixel of the plurality of pixels of the image,wherein the second pixel is adjacent to the first pixel; if the secondpixel is the same color as the first pixel, assigning the second pixelto the first color region; and if the color of the second pixel isdifferent than the color of the first pixel: assigning the second pixelto a second color region, establishing the color of the second pixel asthe color of the second color region, and establishing the coordinatesof the second pixel as the reference coordinates of the second colorregion; and identifying the unidentified object at least in part bycomparing the color regions of the image of the unidentified object withthe color regions of one or more of the images of the plurality of knownobjects.
 26. The apparatus of claim 25, wherein the operation of theprocessor characterizing the unidentified image by dividing the imageinto a plurality of color regions further comprises examining each ofthe remaining pixels of the plurality of pixels of the image andassigning each remaining pixel either to a color region of an adjacentpixel or to a new color region.
 27. The apparatus of claim 25, whereinthe operations of the processor further comprise generating digitalimage data of the unidentified object.
 28. The apparatus of claim 25,wherein the unidentified object comprises a three-dimensional object.29. The apparatus of claim 25, wherein the image capturing devicecaptures the image of the unidentified object as a frame of videosignals.
 30. The apparatus of claim 25, wherein the operations of theprocessor further comprise generating an output response in accordancewith the result of identifying the unidentified object.
 31. Amachine-readable medium having stored thereon data representingsequences of instructions that, when executed by a processor, cause theprocessor to perform operations comprising: capturing an image of eachof a plurality of known objects; characterizing each image of theplurality of known objects by dividing each image into a plurality ofcolor regions; capturing an image of an unidentified object;characterizing the image of the unidentified object by dividing theimage of the unidentified object into a plurality of color regions; andidentifying the unidentified object at least in part by: comparing thecolor regions of the image of the unidentified object with the colorregions of one or more of the images of the plurality of known objects,comparing the number of color regions of each color in the image of theunidentified object to the number of color regions of each color in theimage of the first known object; comparing the size of each color regionof each color in the image of the unidentified object to the size ofeach color region of each color in the image of the first known object;and comparing the relative orientation of each color region of eachcolor in the image of the unidentified object to the relativeorientation of each color region of each color in the image of the firstknown object.
 32. The medium of claim 31, wherein identifying theunidentified object further comprises rejecting the first known objectas the identity of the unidentified object if the number of colorregions, the size of color regions, or the relative orientation of colorregions of the image of the unidentified object and the image of thefirst known object do not match within predetermined tolerances.
 33. Themedium of claim 31, wherein characterizing the image of the unidentifiedobject by dividing the image into a plurality of color regionscomprises: identifying the color of each of a plurality of pixels of theimage; and assigning each of the plurality of pixels of the image to oneof the plurality of color regions of the image.
 34. The medium of claim33, wherein characterizing the image of the unidentified object bydividing the image into a plurality of color regions further comprises:selecting a first pixel of the plurality of pixels of the image andassigning the first pixel to a first color region; establishing thecolor of the first pixel as the color of the first color region;establishing the coordinates of the first pixel as the referencecoordinates of the first color region; selecting a second pixel of theplurality of pixels of the image, wherein the second pixel is adjacentto the first pixel; if the second pixel is the same color as the firstpixel, assigning the second pixel to the first color region; and if thecolor of the second pixel is different than the color of the firstpixel: assigning the second pixel to a second color region, establishingthe color of the second pixel as the color of the second color region,and establishing the coordinates of the second pixel as the referencecoordinates of the second color region.
 35. The medium of claim 34,herein characterizing the image of the unidentified object by dividingthe image into a plurality of color regions further comprises examiningeach of the remaining pixels of the plurality of pixels of the image andassigning each remaining pixel either to a color region of an adjacentpixel or to a new color region.
 36. The medium of claim 31, wherein thedata further comprises instructions causing the processor to performoperations comprising obtaining digital image data for the unidentifiedobject.
 37. The medium of claim 31, wherein the unidentified objectcomprises a three-dimensional object.
 38. The medium of claim 31,wherein capturing the image of the unidentified object comprisescapturing the image of the unidentified object as a frame of videosignals.
 39. The medium of claim 31, the data further comprisesinstructions causing the processor to perform operations comprisinggenerating an output response in accordance with the result ofidentifying the unidentified object.
 40. A machine-readable mediumhaving stored thereon data representing sequences of instructions that,when executed by a processor, cause the processor to perform operationscomprising: capturing an image of each of a plurality of known objects;characterizing each image of the plurality of known objects by dividingeach image into a plurality of color regions; capturing an image of anunidentified object; characterizing the image of the unidentified objectby dividing the image of the unidentified object into a plurality ofcolor regions, comprising: identifying the color of each of a pluralityof pixels of the image, assigning each of the plurality of pixels of theimage to one of the plurality of color regions of the image, selecting afirst pixel of the plurality of pixels of the image and assigning thefirst pixel to a first color region; establishing the color of the firstpixel as the color of the first color region; establishing thecoordinates of the first pixel as the reference coordinates of the firstcolor region; selecting a second pixel of the plurality of pixels of theimage, wherein the second pixel is adjacent to the first pixel; if thesecond pixel is the same color as the first pixel, assigning the secondpixel to the first color region; and if the color of the second pixel isdifferent than the color of the first pixel: assigning the second pixelto a second color region, establishing the color of the second pixel asthe color of the second color region, and establishing the coordinatesof the second pixel as the reference coordinates of the second colorregion; and identifying the unidentified object at least in part bycomparing the color regions of the image of the unidentified object withthe color regions of one or more of the images of the plurality of knownobjects.
 41. The medium of claim 40, wherein characterizing the image ofthe unidentified object by dividing the image into a plurality of colorregions further comprises examining each of the remaining pixels of theplurality of pixels of the image and assigning each remaining pixeleither to a color region of an adjacent pixel or to a new color region.42. The medium of claim 40, wherein the data further comprisesinstructions causing the processor to perform operations comprisingobtaining digital image data for the unidentified object.
 43. The mediumof claim 40, wherein the unidentified object comprises athree-dimensional object.
 44. The medium of claim 40, wherein capturingthe image of the unidentified object comprises capturing the image ofthe unidentified object as a frame of video signals.
 45. The medium ofclaim 40, the data further comprises instructions causing the processorto perform operations comprising generating an output response inaccordance with the result of identifying the unidentified object.